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PUBLICATIONS

O-RAN with Machine Learning in ns-3

Published

Author(s)

Wesley Garey, Tanguy Ropitault, Richard A. Rouil, Evan Black, Weichao Gao

Abstract

The Open Radio Access Network (O-RAN) Alliance is an industryled standardization effort, with the main objective of evolving the Radio Access Network (RAN) to be open, intelligent, interoperable, and autonomous to support the ever growing need of improved performance and flexibility in mobile networks. This paper introduces an extension to Network Simulator 3 (ns-3) which mimics the behavior and components of the O-RAN Alliance's O-RAN architecture. In this paper, we will describe the O-RAN architecture, our model in ns-3, and a Long Term Evolution (LTE) case study that utilizes Machine Learning (ML) and its integration with ns-3. At the end of this paper, the reader will have a general understanding of O-RAN and the capabilities of our fully simulated contribution so it can be leveraged to design and evaluate O-RAN-based solutions
Citation
WNS3 2023 Program
Pub Weblink
https://www.nsnam.org/research/wns3/wns3-2023/program/
Pub Type
Websites

Download Paper

Local Download
Software research, Open Radio Access Network (Open-RAN), Next generation networks and Mobile and wireless networking

Citation

Garey, W. , Ropitault, T. , Rouil, R. , Black, E. and Gao, W. (2023), O-RAN with Machine Learning in ns-3, WNS3 2023 Program, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956908, https://www.nsnam.org/research/wns3/wns3-2023/program/ (Accessed October 7, 2025)

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Created December 11, 2023
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